An estimated 75% of business executives believe that artificial intelligence will be implemented actively in companies over the next three years.
The future of machine intelligence is here and can be seen everywhere from health care to finance and security. Businesses that will implement AI-powered systems in their operations will see improved production, sales, and customer engagement.
Customer support and customer engagement is an integral part of e-commerce businesses with statistics showing that nearly 50% of online customers leave their shopping carts if they can’t get fast answers to questions they have about the product or service. With many businesses turning their attention to the opportunities that AI has to offer, we should expect to see nearly all customer relations being handled by intelligent machines in the next few years.
In this article, we will discuss why machine intelligence is important in boosting customer engagement, ways it is being implemented, and some examples of companies reaping big in profits using this tech to enhance their customers’ experience.
Why is artificial intelligence in customer experience needed?
According to Temkin Group, a typical $1 billion firm can gain up to $775 million in three years by modestly improving their CX. That means there is a strong connection between buyer experience and sales/conversions. Excellent customer service drives growth while poor client support may lead to failure.
But as much as people agree that client experience is a significant factor in purchasing decisions, only 49% of consumers in the US today say that companies offer good customer experience. Studying patterns and behavior from customer data can help businesses to enhance their customers’ experiences. However, interpreting huge amounts of data is overwhelming for employers. These reasons are why there is a need for AI systems in customer relations and experience.
Sales and customer support agents can’t keep up with each customer’s entire history with the company let alone derive useful insights from such data in real time. But AI-powered automated systems can:
- Identify more accurate buyer patterns.
- Deliver enhanced customer service in different company touchpoints.
- Respond to customers faster at all times.
How machines are being used to improve customer experience
Any company that intends to leverage neural networks to enhance customer engagement should understand data unification, insights delivery in real-time and the business context. Let’s dig deeper into these terms.
Unification of data
Unlike the past where bringing together massive amounts of data (data unification) would take weeks, now it just takes days. AI-based data unification tools make the tedious task of performing customer journey analytics faster, cheaper and less stressful.
For intelligent machines to make meaningful impacts on customer relations, insights must be conveyed in real-time. Though far from being customary, SaaS platforms can use real-time insights to deliver better client experience at their various touchpoints using APIs. Customer analytics platforms are already offering these options for businesses.
Neural networks must be given context; that is, the importance of particular events in shaping or predicting customer behavior. They must be aware of the unique journey of each customer and their corresponding behavior to predict the next best action.
The more customized your service is, the more satisfied your customers are. Through data and behavioral analytics, artificial intelligence technology has the power to provide more personalized services and help you engage with customers better. Here intelligent systems can help you:
Collect as much valuable data as possible
You must know your clients before you can respond to their needs and demands. That is why collecting customer data is important. For a business to thrive, it must continually engage with their clients and know their needs, challenges, and experience with the brand. Engaging with and getting feedback from customers can be overwhelming and sometimes impossible if the customer base is big. The good thing, however, is that you don’t need to hire workers for these tasks. Big data is where AI-based systems thrive. And a business collects this data every day through machine interactions with potential and existing customers.
Familiarize and understand your customers
Once the data is gathered, it must be analyzed to extract valuable information. However, a Forrester Research study found that many companies analyze just 12% of their total data and miss out on valuable insights from 88% of the data ignored. It may be that the businesses collect data but don’t know what to do with it or they lack the right expertise or systems to interpret it. AI-enabled customer analytics can help you better utilize massive amounts of otherwise unintelligible data. Data collected from customer interactions can be packed and interpreted by these systems. With these insights, you can see the bigger picture more clearly and better understand how to improve your relations with customers.
Anticipate their needs
“95% of consumers share their bad experiences with a brand with others. Furthermore, 67% of consumers would be willing to pay more for a great experience. For businesses or marketers to provide better service faster, they must invest in acquiring intimate knowledge about customer needs, preferences, and behaviors,” says Andrew Ortiz, a marketing specialist at Skillroads.
Knowing what your different customer journeys will help you gain leverage over your competitors. When you know your customers, you can formulate smart business strategies to engage and retain them. Moreover, as you continue to interact with them through AI-powered chatbots, the easier it will be to predict their needs, create personalized experiences and build their loyalty. Remember, 48% of customers are unlikely to buy from a brand again if they had a bad experience.
AI applications are changing the face of customer service
The biggest impact of intelligent systems in business so far is automating most of the mundane tasks previously done by customer care agents, sales and marketing personnel and other employees dealing with customers. Here are two smart applications that have revolutionized customer engagement:
The global chatbot market is predicted to reach a whopping $1.23 billion by the year 2025 recording 24.3% compounded annual growth rate. That said, chatbots – which are essentially conversational machine agent s- can be implemented in various customer service points. Their effectiveness stems from their ability to simulate real human responses/interactions and give quick responses to customer queries. Bots are especially useful for companies that desire to offer 24/7 support to their clients. They eliminate delays, and error in dealing with customer concerns and complaints.
A VA is an AI-enabled personal assistant that performs tasks or delivers services to an individual based on their voice commands. They can understand and respond to complex conversations, recommend things, items or places, or remind users of events. Examples of these intelligent assistants: Microsoft’s Cortana, Google Assistant, and Apple’s Siri.
Examples of companies taking the lead in AI in CX
Companies in various industries are increasingly experimenting with AI-enabled systems to gain customer insights and as such, predict their behavior and boost their experience. And it is safe to say that they are reaping great rewards from their effort. These benefits include improved customer relations, increased client lifetime value and reduced leakage in the sales funnel. Check out some examples of companies using intelligent tech to improve customer engagement.
Domino’s Pizza bot on Facebook Messenger
Domino’s decided to make ordering a pizza easier than ever by building a bot named “Dom” on Facebook Messenger. Now, their customers only need to send the bot a message with the word pizza to start the ordering process. The chatbot immediately takes the customer’s details and makes their order. With the bot in place, completing an order has become easier and faster than visiting the restaurant or calling a customer care agent.
Sephora’s virtual artist
Sephora is one of the few beauty stores that has effectively leveraged the use of machine intelligence in dealing with customers. Their AI-powered Virtual Artist, available of their site or app, allows visitors to try out different products like eyeshadows, foundations, toners, highlighters or lipsticks to find those that match their skins’ tones or preferences. A Virtual Artist bot is also available. Users can send their picture to the bot and get it back with the new look after the recommended products are applied.
The tool brings together all of Sephora’s products seamlessly and can make real-time offers and recommendations to users. Once the customer decides to buy, their checkout procedure is smooth and quick.
Spotify’s AI-enabled music recommendations
Spotify music streaming business is almost entirely based on data. But with AI-based technology, the brand has taken user experience to the next level. Their site can store massive customer data, and analyze it to find patterns and predict the kind of music individual customers will like. Spotify users get personalized playlists recommendations every week from their data. To say this strategy is effective is an understatement – the music service is highly-reviewed for its effectiveness in predicting the tastes and moods of its users.
Black Diamond equipment’s predictive AI-based system
Black Diamond Equipment is a go-to store for buying skiing equipment for may skiers. And the retailer has made a mark for themselves by leveraging intelligent systems to offer personalized customer engagement and recommendations for every customer. The company uses complex analytics to find insights from customers buying history and combines them with other relevant information – such as the weather – to make real-time customized recommendations. Their system has seen a drop in abandoned carts and an increase in conversions.
Key takeaway on machines enhancing customer experience
Machine learning algorithms have the potential to make customer service, engagement and experience better. With little effort and investment, companies can understand, remember and respond to customer’s queries, and complaints in a meaningful manner. The challenge of building these systems fast enough to experience the benefits, however, remains. With the shortage of talent in data science and the difficulty of making different systems ready for this new technology have made implementation problematic for many businesses.
But more and more companies now realize the opportunity AI-based systems present in enhancing the customer journey. According to Adobe, 47% of digitally established organizations said they have a machine intelligence strategy. That said, the implementation of smart systems in business across all industries is set to snowball over the coming years. So, any company that wants to stay afloat, let alone remain profitable, must consider this technology in its business strategy.
Alice Berg is a blogger and career advisor, who helps people to find their own way in life, gives career advice and guidance, helps young people to prepare for their careers. You can find Alice on Twitter and Medium.